Research Paper|Volume 12, Issue 14|pp 14933—14948

A new survival model based on ferroptosis-related genes for prognostic prediction in clear cell renal cell carcinoma

Guangzhen Wu¹, Qifei Wang¹, Yingkun Xu², Quanlin Li¹, Liang Cheng^3,⁴

¹Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
²Department of Urology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
³Department of Pathology and Laboratory Medicine, Indianapolis, IN 46202, USA
⁴Department of Urology, Indiana University School of Medicine, Indianapolis, IN 46202, USA

* Equal contribution

Received: March 17, 2020Accepted: June 4, 2020Published: July 20, 2020

Copyright: © 2020 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

In this study, we analyzed the clinical significance of ferroptosis-related genes (FRGs) in 32 cancer types in the GSCA database. We detected a 2-82% mutation rate among 36 FRGs. In clear cell renal cell carcinoma (ccRCC; n=539) tissues from the The Cancer Genome Atlas database, 30 of 36 FRGs were differentially expressed (up- or down-regulated) compared to normal kidney tissues (n=72). Consensus clustering analysis identified two clusters of FRGs based on similar co-expression in ccRCC tissues. We then used LASSO regression analysis to build a new survival model based on five risk-related FRGs (CARS, NCOA4, FANCD2, HMGCR, and SLC7A11). Receiver operating characteristic curve analysis confirmed good prognostic performance of the new survival model with an area under the curve of 0.73. High FANCD2, CARS, and SLC7A11 expression and low HMGCR and NCOA4 expression were associated with high-risk ccRCC patients. Multivariate analysis showed that risk score, age, stage, and grade were independent risk factors associated with prognosis in ccRCC. These findings demonstrate that this five risk-related FRG-based survival model accurately predicts prognosis in ccRCC patients, and suggest FRGs are potential prognostic biomarkers and therapeutic targets in several cancer types.